Evolving Trends in Prompt Engineering for Large Language Models (LLMs) with Built-in Responsible AI Practices
Discover the evolution of Prompt Engineering for Large Language Models (LLMs) and their Built-in Responsible AI Practices with Jayachandran Ramachandran and Rohit Sroch. Join us for an insightful discussion titled “Evolving Trends in Prompt Engineering for Large Language Models (LLMs) with Built-in Responsible AI Practices.”
The advent of LLMs like GPT, Llama, PaLM has revolutionized AI, offering unique capabilities in enterprise search, summarization, conversational bots, and more. Organizations harness these LLMs through prompt engineering and fine-tuning, but challenges persist. In this talk, explore the cutting-edge dimensions of LLMs, including Prompt Engineering, Evaluation, Model Optimization & Deployment, and Responsible AI, and gain valuable insights into the evolving landscape of AI technologies.
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Previous ODSC Video of the Week
Large Language Models Are Not (Necessarily) Generative Ai – Karin Verspoor, PhD
Gain a precise understanding of Large Language Models with Professor Karin Verspoor, Dean of the School of Computing Technologies at RMIT University’s talk titled “Large Language Models Are Not (Necessarily) Generative AI,”. Karin Verspoor delves into the distinctions between LLMs and generative models.
She will clarify what constitutes an LLM, explores various architectures, and helps you discern when an LLM qualifies as a generative model. By the end of this session, you’ll have an in-depth grasp of the inner workings of these models and the specific natural language processing challenges they are designed to address.
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